1. Field of the Invention
Embodiments of the present invention generally relate to preprocessing of stereo images.
2. Description of the Related Art
Objects at different depths in the scene of a stereoscopic video sequence will have different displacements, i.e., disparities, in left and right frames of the stereoscopic video sequence, thus creating a sense of depth when the stereoscopic images are viewed on a stereoscopic display. The term disparity refers to the shift that occurs at each pixel in a frame between the left and right images due the different perspectives of the cameras used to capture the two images. The amount of shift or disparity may vary from pixel to pixel depending on the depth of the corresponding 3D point in the scene.
In many stereo vision applications, it is important to know the depths of objects in a scene. The depth information for a stereo frame or image is typically computed from the disparities between the pixels in the left image and corresponding pixels in the right image because depth is proportional to the reciprocal of the disparity. To determine the disparities, a stereo matching algorithm is applied to a stereo image.
Further, in many applications, the stereo images are filtered before the images are analyzed for correspondence by the stereo matching algorithm. The purpose of this filtering step may be to filter out the low-frequency image signal that tends to capture undesired illumination and exposure differences between the stereo cameras, to amplify the high-frequency texture of the scene to facilitate the stereo matching process, and/or to reduce the effect of image sensor noise.
A number of stereo image pre-processing techniques implement the above ideas to make stereo matching algorithms more robust against noise and illumination. In particular, the Laplacian-of-Gaussian (LoG) filter as described in D. Marr and E. Hildreth, “Theory of Edge Detection”, Proceedings of the Royal Society of London, Series B, Biological Sciences, Vol. 207, No. 1167, Feb. 29, 1980, pp. 187-217 (Marr herein), and efficient variants and approximations thereof such as those described in Soo-Chang Pei and Ji-Hwei Horng, “Design of FIR Bilevel Laplacian-of-Gaussian Filter”, Signal Processing, Vol. 82, Issue 4, April 2002, pp. 677-691, are very popular.